Think tank · Research orgs · Berkeley, CA · Est. 2019
Convergence Analysis is a US-based (fiscal address in Berkeley, CA) non-profit AI safety and AI-governance research organization focused on transformative-AI risk reduction. The organization’s stated mission is to design a safe and flourishing future for humanity through strategic, sociotechnical research and advocacy aimed at mitigating existential risk from AI.
Convergence describes its approach as outcome-driven and organized around (1) research into AI scenarios and threat models, (2) governance research to identify actionable policy and institutional strategies, and (3) “AI awareness” activities intended to spread findings to policymakers and the general public. The organization also reports running field-building and coordination initiatives (e.g., an AI Scenarios Network) and publishing scenario/governance “reporting corpora” intended to be used by decision-makers and the broader AI safety community. In terms of institutional role, Convergence positions itself as a “strategy research” and governance analysis institute that can both publish technical policy research and consult with government processes. In its 2024 impact review, Convergence states that it provided consultation to the US Bureau of Industry and Security and that specific recommendations were incorporated into the EU’s GPAI Code of Practice, alongside other channels of academic and policy influence. Strategically, Convergence’s current public research outputs emphasize concrete governance mechanisms (e.g., AI model registries and related measurement/enforcement proposals), plus “readiness” frameworks (e.g., the AI Readiness Objectives) that aim to help governments assess sufficiency across categories of AI security interventions.
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We conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Convergence 2024 Impact ReviewWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Conference Summary: Threshold 2030 - Modeling AI Economic FuturesWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
New Report: 2024 State of the AI Regulatory LandscapeWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
New Report: Evaluating an AI Chip Registration PolicyWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Announcing Convergence Analysis: An Institute for AI Scenario & Governance ResearchWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
The AI Readiness Objectives Towards Sufficiency in National AI Security StrategiesWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Pathways to short TAI timelinesThis report explores pathways through which transformative AI (TAI) could be developed within the next ten years (‘short TAI timelines’). It examines compute scaling and recursive improvement as key mechanisms for AI capabilities progress, describes seven distinct scenarios with
The Manhattan Trap Why a Race to Artificial Superintelligence is Self-DefeatingThis paper examines the strategic dynamics of international competition to develop Artificial Superintelligence (ASI).
Training Data Attribution (TDA) Examining Its Adoption & Use CasesTDA techniques aim to identify training data points that are especially influential on the behavior of specific model outputs. This report investigates Training Data Attribution (TDA) and its potential importance to and tractability for reducing extreme risks from AI.
Analysis of Global AI Governance StrategiesWe analyze three prominent strategies for governing transformative AI (TAI) development: Cooperative Development, Strategic Advantage, and Global Moratorium. We evaluate these strategies across varying levels of alignment difficulty and development timelines, examining their effe
The brave new world of AI Implications for public sector agents, organisations, and governanceWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Convergence publishes the AI Readiness Objectives framework, described as a set of 7 aspirational goals intended to represent the objectives of AI security interventions and help governments reason about readiness/sufficiency.
Tactical Guidance on AI-Integrated Education & TrainingConvergence publishes a policy brief providing a roadmap for education and training system adaptation to AI disruption, framed around avoiding cognitive dependency and building a human-centric workforce.
The Iron House: Geopolitical Stakes of the US-China AGI RaceConvergence publishes a fellowship-related piece arguing that geopolitical rivalry around AGI could produce catastrophic collapse risks as well as prosperity depending on decisions and dynamics.
Convergence Analysis' recommendations for the US AI Action PlanConvergence publishes its submitted recommendations to OSTP’s RFI for a national AI Action Plan, focusing on economic policy, national security and innovation, AI diplomacy, and information about powerful dual-use models.
Convergence 2024 Impact ReviewConvergence publishes its impact review describing outputs, claimed regulatory influence and outreach metrics, operations, and 2024 funding figures and runway assumptions.
Convergence publishes a report proposing implementation of national AI model registries as a governance foundation, including design, implementation, and enforcement considerations.